The existing monitoring technologies of obstructive sleep apnea/hypopnea syndrome (OSAHS) face many problems, such as invasion discomfort and privacy security. Aiming at these problems, non-contact microphone array technology is utilized in this work. Firstly, two microphones on both sides of the bedhead are used to synchronously acquire the snoring signals of the patient all night. Secondly, the high-band energy ratio (HER) and spatial cross-correlation deviation (SCCD) between the two array element channels are proposed as the spatial propagation features of snoring. Thirdly, the supine and lateral positions are indirectly recognized by the head orientation classification through unsupervised clustering, which provides a new feasible idea for the detection of sleep body positions.
Aiming at the problem that the Acoustic Diversity Index (ADI) obtained from the marginal area of the nature reserve is easily affected by the noise of human activities outside the area, the advantages of the Differential Microphone Array (DMA) that has low processing complexity and can rapidly form full-band spatial notch are used. Firstly, two sets of backto-back dual-delay DMAs with coprime delay factors are applied to adaptively filter out the anthropogenic noise from a fixed direction. Then, the two sets of spatial filtering outputs are used to suppress the grating lobe effect of the highfrequency pattern of DMAs based on the notch interleaving features in the two-dimensional space consisting of angle and frequency. Finally, the 0-1 detection component of the biotic signal is reconstructed at all time-frequency bins by taking the larger one between the two values, so as to restore the ideal ADI in the whole space without anthropogenic noise. It will provide a feasible idea for robust and accurate monitoring and evaluation of biological acoustic diversity in areas close to human activities.
Aiming at the performance analysis of portable planar microphone arrays under different attitude angles in practical applications, azimuth estimation error of sound source associated with array attitude angle is derived. The influence from pitch angle and roll angle is formulated as an impact factor and the corresponding investigation is provided, leading to an explicit relationship between azimuth estimation error bound and tolerance range of array attitude angle. Comparison analysis and numerical results demonstrate that this study provides a quantitative approach to evaluate the azimuth estimation performance for portable planar microphone arrays when attitude angle is considered.
KEYWORDS: Artillery, Atmospheric propagation, Wave propagation, Interference (communication), Acoustics, Distortion, Signal attenuation, Wind energy, Signal to noise ratio, Signal processing
Owing to the complexity of sound propagation and the limitations of available samples, traditional artillery sound recognition methods are lack of generalization ability to arbitrary acoustic propagation environments and detection ranges. In this paper, a novel classification approach is proposed based on the deterministic linear channel model of sound propagation in the atmosphere, which identifies the type of an unknown remote artillery sound by searching the matched source waveform space with the maximum projection energy in a pre-established database. Simulation results show that the proposed method has higher adaptability to the variation of atmospheric propagation channels of the acoustic signal, and provides a feasible idea for improving the ability of long-range artillery sound recognition at any unknown distances.
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